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Including Sentinel-1 radar data to improve the disaggregation of MODIS land surface temperature data / Abdelhakim Amazirh in ISPRS Journal of photogrammetry and remote sensing, vol 150 (April 2019)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 150 (April 2019) . - pp 11 - 26 Titre : Including Sentinel-1 radar data to improve the disaggregation of MODIS land surface temperature data Type de document : Article/Communication Auteurs : Abdelhakim Amazirh, Auteur ; Olivier Merlin, Auteur ; Salah Er-Raki, Auteur Année de publication : 2019 Article en page(s) : pp 11 - 26 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes descripteurs IGN] désagrégation [Termes descripteurs IGN] humidité du sol [Termes descripteurs IGN] image à haute résolution [Termes descripteurs IGN] image Landsat [Termes descripteurs IGN] image Landsat-8 [Termes descripteurs IGN] image Sentinel-SAR [Termes descripteurs IGN] image Terra-MODIS [Termes descripteurs IGN] Maroc [Termes descripteurs IGN] modèle de transfert radiatif [Termes descripteurs IGN] réflectance spectrale [Termes descripteurs IGN] régression multiple [Termes descripteurs IGN] température au sol [Termes descripteurs IGN] zone semi-aride Résumé : (Auteur) The use of land surface temperature (LST) for monitoring the consumption and water status of crops requires data at fine spatial and temporal resolutions. Unfortunately, the current spaceborne thermal sensors provide data at either high temporal (e.g. MODIS: Moderate Resolution Imaging Spectro-radiometer) or high spatial (e.g. Landsat) resolution separately. Disaggregating low spatial resolution (LR) LST data using ancillary data available at high spatio-temporal resolution could compensate for the lack of high spatial resolution (HR) LST observations. Existing LST downscaling approaches generally rely on the fractional green vegetation cover (fgv) derived from HR reflectances but they do not take into account the soil water availability to explain the spatial variability in LST at HR. In this context, a new method is developed to disaggregate kilometric MODIS LST at 100 m resolution by including the Sentinel-1 (S-1) backscatter, which is indirectly linked to surface soil moisture, in addition to the Landsat-7 and Landsat-8 (L-7 & L-8) reflectances. The approach is tested over two different sites – an 8 km by 8 km irrigated crop area named “R3” and a 12 km by 12 km rainfed area named “Sidi Rahal” in central Morocco (Marrakech) – on the seven dates when S-1, and L-7 or L-8 acquisitions coincide with a one-day precision during the 2015–2016 growing season. The downscaling methods are applied to the 1 km resolution MODIS-Terra LST data, and their performance is assessed by comparing the 100 m disaggregated LST to Landsat LST in three cases: no disaggregation, disaggregation using Landsat fgv only, disaggregation using both Landsat fgv and S-1 backscatter. When including fgv only in the disaggregation procedure, the mean root mean square error in LST decreases from 4.20 to 3.60 °C and the mean correlation coefficient (R) increases from 0.45 to 0.69 compared to the non-disaggregated case within R3. The new methodology including the S-1 backscatter as input to the disaggregation is found to be systematically more accurate on the available dates with a disaggregation mean error decreasing to 3.35 °C and a mean R increasing to 0.75. Numéro de notice : A2019-136 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2019.02.004 date de publication en ligne : 15/02/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.02.004 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92467 [article]

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ICARE-VEG: A 3D physics-based atmospheric correction method for tree shadows in urban areas / Karine R.M. Adeline in ISPRS Journal of photogrammetry and remote sensing, vol 142 (August 2018)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 142 (August 2018) . - pp 311 - 327 Titre : ICARE-VEG: A 3D physics-based atmospheric correction method for tree shadows in urban areas Type de document : Article/Communication Auteurs : Karine R.M. Adeline, Auteur ; Xavier Briottet , Auteur ; X. Ceamanos, Auteur ; T. Dartigalongue, Auteur ; Jean-Philippe Gastellu-Etchegorry, Auteur Année de publication : 2018 Article en page(s) : pp 311 - 327 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes descripteurs IGN] arbre (flore) [Termes descripteurs IGN] correction atmosphérique [Termes descripteurs IGN] détection d'ombre [Termes descripteurs IGN] houppier [Termes descripteurs IGN] image à très haute résolution [Termes descripteurs IGN] image hyperspectrale [Termes descripteurs IGN] Leaf Area Index [Termes descripteurs IGN] logiciel de traitement d'image [Termes descripteurs IGN] modèle de transfert radiatif [Termes descripteurs IGN] modélisation 3D [Termes descripteurs IGN] réflectance végétale [Termes descripteurs IGN] zone urbaine Résumé : (Auteur) Many applications dedicated to urban areas (e.g. land cover mapping and biophysical properties estimation) using high spatial resolution remote sensing images require the use of 3D atmospheric correction methods, able to model complex light interactions within urban topography such as buildings and trees. Currently, one major drawback of these methods is their lack in modeling the radiative signature of trees (e.g. the light transmitted through the tree crown), which leads to an over-estimation of ground reflectance at tree shadows. No study has been carried out to take into account both optical and structural properties of trees in the correction provided by these methods. The aim of this work is to improve an existing 3D atmospheric correction method, ICARE (Inversion Code for urban Areas Reflectance Extraction), to account for trees in its new version, ICARE-VEG (ICARE with VEGetation). After the execution of ICARE, the methodology of ICARE-VEG consists in tree crown delineation and tree shadow detection, and then the application of a physics-based correction factor in order to perform a tree-specific local correction for each pixel in tree shadow. A sensitivity analysis with a design of experiments performed with a 3D canopy radiative transfer code, DART (Discrete Anisotropic Radiative Transfer), results in fixing the two most critical variables contributing to the impact of an isolated tree crown on the radiative energy budget at tree shadow: the solar zenith angle and the tree leaf area index (LAI). Thus, the approach to determine the correction factor relies on an empirical statistical regression and the addition of a geometric scaling factor to account for the tree crown occultation from ground. ICARE-VEG and ICARE performance were compared and validated in the Visible-Near Infrared Region (V-NIR: 0.4–1.0 µm) with hyperspectral airborne data at 0.8 m resolution on three ground materials types, grass, asphalt and water. Results show that (i) ICARE-VEG improves the mean absolute error in retrieved reflectances compared to ICARE in tree shadows by a multiplicative factor ranging between 4.2 and 18.8, and (ii) reduces the spectral bias in reflectance from visible to NIR (due to light transmission through the tree crown) by a multiplicative factor between 1.0 and 1.4 in terms of spectral angle mapper performance. ICARE-VEG opens the way to a complete interpretation of remote sensing images (sunlit, shade cast by both buildings and trees) and the derivation of scientific value-added products over all the entire image without the preliminary step of shadow masking. Numéro de notice : A2018-296 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.05.015 date de publication en ligne : 01/08/2018 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.05.015 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90415 [article]

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Understanding the temporal dimension of the red-edge spectral region for forest decline detection using high-resolution hyperspectral and Sentinel-2a imagery / Pablo J. Zarco-Tejada in ISPRS Journal of photogrammetry and remote sensing, vol 137 (March 2018)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 137 (March 2018) . - pp 134 - 148 Titre : Understanding the temporal dimension of the red-edge spectral region for forest decline detection using high-resolution hyperspectral and Sentinel-2a imagery Type de document : Article/Communication Auteurs : Pablo J. Zarco-Tejada, Auteur ; Non-répertorié, Auteur ; Rocío Hernández-Clemente, Auteur ; Non-répertorié, Auteur Année de publication : 2018 Article en page(s) : pp 134 - 148 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes descripteurs IGN] bande rouge [Termes descripteurs IGN] défoliation [Termes descripteurs IGN] données spatiotemporelles [Termes descripteurs IGN] image hyperspectrale [Termes descripteurs IGN] image Sentinel-MSI [Termes descripteurs IGN] modèle de transfert radiatif [Termes descripteurs IGN] Normalized Difference Vegetation Index [Termes descripteurs IGN] Pinus (genre) [Termes descripteurs IGN] santé des forêts [Termes descripteurs IGN] teneur en chlorophylle des feuilles Résumé : (Auteur) The operational monitoring of forest decline requires the development of remote sensing methods that are sensitive to the spatiotemporal variations of pigment degradation and canopy defoliation. In this context, the red-edge spectral region (RESR) was proposed in the past due to its combined sensitivity to chlorophyll content and leaf area variation. In this study, the temporal dimension of the RESR was evaluated as a function of forest decline using a radiative transfer method with the PROSPECT and 3D FLIGHT models. These models were used to generate synthetic pine stands simulating decline and recovery processes over time and explore the temporal rate of change of the red-edge chlorophyll index (CI) as compared to the trajectories obtained for the structure-related Normalized Difference Vegetation Index (NDVI). The temporal trend method proposed here consisted of using synthetic spectra to calculate the theoretical boundaries of the subspace for healthy and declining pine trees in the temporal domain, defined by CItime=n/CItime=n+1 vs. NDVItime=n/NDVItime=n+1. Within these boundaries, trees undergoing decline and recovery processes showed different trajectories through this subspace. The method was then validated using three high-resolution airborne hyperspectral images acquired at 40 cm resolution and 260 spectral bands of 6.5 nm full-width half-maximum (FWHM) over a forest with widespread tree decline, along with field-based monitoring of chlorosis and defoliation (i.e., ‘decline’ status) in 663 trees between the years 2015 and 2016. The temporal rate of change of chlorophyll vs. structural indices, based on reflectance spectra extracted from the hyperspectral images, was different for trees undergoing decline, and aligned towards the decline baseline established using the radiative transfer models. By contrast, healthy trees over time aligned towards the theoretically obtained healthy baseline. The applicability of this temporal trend method to the red-edge bands of the MultiSpectral Imager (MSI) instrument on board Sentinel-2a for operational forest status monitoring was also explored by comparing the temporal rate of change of the Sentinel-2-derived CI over areas with declining and healthy trees. Results demonstrated that the Sentinel-2a red-edge region was sensitive to the temporal dimension of forest condition, as the relationships obtained for pixels in healthy condition deviated from those of pixels undergoing decline. Numéro de notice : A2018-079 Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.01.017 date de publication en ligne : 17/02/2018 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.01.017 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89441 [article]

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The potential of multifrequency SAR images for estimating forest biomass in Mediterranean areas / Emanuele Santi in Remote sensing of environment, vol 200 (October 2017)  

Public [article]  inRemote sensing of environment > vol 200 (October 2017) . - pp 63 - 73 Titre : The potential of multifrequency SAR images for estimating forest biomass in Mediterranean areas Type de document : Article/Communication Auteurs : Emanuele Santi, Auteur ; Simonetta Paloscia, Auteur ; Simone Pettinato, Auteur ; et al., Auteur Année de publication : 2017 Article en page(s) : pp 63 - 73 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes descripteurs IGN] bande C [Termes descripteurs IGN] bande L [Termes descripteurs IGN] biomasse forestière [Termes descripteurs IGN] capacité de stockage [Termes descripteurs IGN] classification par réseau neuronal [Termes descripteurs IGN] forêt méditerranéenne [Termes descripteurs IGN] image ALOS-PALSAR [Termes descripteurs IGN] image Envisat-ASAR [Termes descripteurs IGN] image radar moirée [Termes descripteurs IGN] modèle de transfert radiatif [Termes descripteurs IGN] production primaire brute [Termes descripteurs IGN] Toscane (Italie) Résumé : (auteur) The extraction of forest information from SAR images is particularly complex in Mediterranean areas, since they are characterized by high spatial fragmentation and heterogeneity. We have investigated the use of multi-frequency SAR data from different sensors (ALOS/PALSAR and ENVISAT/ASAR) for estimating forest biomass in two test areas in Central Italy (San Rossore and Molise), where detailed in-situ measurements and Airborne Laser Scanning (ALS) data were available. The study focused on the estimation of growing stock volume (GS, in m3/ha) by using an inversion algorithm based on artificial neural networks (ANN). The ANN algorithm was first appropriately trained using the available GS estimates obtained from ALS data. The potential of this algorithm was then improved through the innovative use of a simulated dataset, generated by a forward electromagnetic model based on the Radiative Transfer Theory (RTT). The algorithm is able to merge SAR data at L and C bands for predicting GS in diversified Mediterranean environments. The performed analyses indicated that GS was correctly estimated by integrating information from L and C bands on both test areas, with the following statistics: R > 0.97 and RMSE = 28.5 m3/ha for the independent test, and R = 0.86 and RMSE ≈ 77 m3/ha for the final independent validation, the latter performed on the forest stands of both areas not included in the ALS acquisitions and where conventional measurements were available. The research then illustrates the potential of using the obtained GS estimates from SAR data to drive the simulations of forest net primary production (NPP). This experiment produced spatially explicit estimates of GS current annual increments that are slightly less accurate than those obtained from ground observations (R = 0.75 and RMSE ≈ 1.5 m3/ha/year). Numéro de notice : A2017-415 Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern En ligne : https://doi.org/10.1016/j.rse.2017.07.038 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86307 [article]

Retrieving grassland canopy water content by considering the information from neighboring pixels / Binbin He in Photogrammetric Engineering & Remote Sensing, PERS, vol 83 n° 8 (August 2017)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 83 n° 8 (August 2017) . - pp 553 - 565 Titre : Retrieving grassland canopy water content by considering the information from neighboring pixels Type de document : Article/Communication Auteurs : Binbin He, Auteur ; Xingwen Quan, Auteur ; Dasong Xu, Auteur ; et al., Auteur Année de publication : 2017 Article en page(s) : pp 553 - 565 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes descripteurs IGN] approche pixel [Termes descripteurs IGN] Chine [Termes descripteurs IGN] classification barycentrique [Termes descripteurs IGN] modèle de transfert radiatif [Termes descripteurs IGN] prairie [Termes descripteurs IGN] réponse spectrale [Termes descripteurs IGN] teneur en eau liquide Résumé : (auteur) Accurate and robust retrieval of grassland canopy water content (CWC) using a radiative transfer model (RTM) is generally affected by the ill-posed inversion problem due to the lack of enough available a priori information. To alleviate this problem when inversing the RTM, a two-step inversion method was proposed. The key point of this method was to simultaneously consider the spectral information from neighboring pixels and the spatial dependency among these pixels, with the purpose to win more information from these neighboring pixels. The proposed methodology was then applied to retrieve CWC using the PROSAIL RTM from Landsat-8 OLI data for a plateau grassland in China. The results showed that the estimated CWC using the proposed method (RMSE = 67.31 g m-2 and R2 = 0.81) was better than that from the traditional method (RMSE = 80.11 g m-2 and R2 = 0.78) which only considered the information of single pixel. Numéro de notice : A2017-436 Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.83.8.553 En ligne : https://doi.org/10.14358/PERS.83.8.553 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86340 [article]

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Simultaneous estimation of leaf area index, fraction of absorbed photosynthetically active radiation, and surface albedo from multiple-satellite data / Han Ma in IEEE Transactions on geoscience and remote sensing, vol 55 n° 8 (August 2017)  

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Télédétection pour l'observation des surfaces continentales, Volume 3. Observation des surfaces continentales par télédétection 1 / Nicolas Baghdadi (2017)

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Evaluating leaf chlorophyll content prediction from multispectral remote sensing data within a physically-based modelling framework / H. Croft in ISPRS Journal of photogrammetry and remote sensing, vol 102 (April 2015)  

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On the SAR backscatter of burned forests: a model-based study in C-Band, over burned pine canopies full text / Vasileios kalogirou in IEEE Transactions on geoscience and remote sensing, vol 52 n° 10 tome 1 (October 2014)

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Laboratory measurements of plant drying: Implications to estimate moisture content from radiative transfer models in two temperate species / Sara Jurdao in Photogrammetric Engineering & Remote Sensing, PERS, vol 80 n° 5 (May 2014)  

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Improvement and application of the conifer forest multiangular hybrid GORT model MGeoSAIL / Qiang Wang in IEEE Transactions on geoscience and remote sensing, vol 51 n° 10 (October 2013)

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Spectral response function comparability among 21 satellite sensors for vegetation monitoring / Alemu Gonsamo in IEEE Transactions on geoscience and remote sensing, vol 51 n° 3 Tome 1 (March 2013)

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A semi-analytical model for multitemporal prediction of chlorophyll-a in an Iowa lake using Hyperion data / R. Sugumaran in Photogrammetric Engineering & Remote Sensing, PERS, vol 78 n° 12 (December 2012)  

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A new 3-D solar radiation model for 3-D city models / Jaroslav Hofierka in Transactions in GIS, vol 16 n° 5 (October 2012)

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Kalideos ADAM : synthèse et retour d'expérience / R. Vintila in Revue Française de Photogrammétrie et de Télédétection, n° 197 (Juin 2012)

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